VM Migration SLA Violation Prediction Using Capacity Factors
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Solution Overview
Problem
Current resource management frameworks lack techniques to evaluate and prevent Service Level Agreement (SLA) violations during workload migration from physical to virtualized environments, and fail to estimate the required capacity in the target infrastructure to meet SLA parameters, leading to potential SLA violations and inefficient infrastructure utilization.
Innovation Solution
A method and apparatus that use capacity factors, service rate changes, and utilization thresholds to predict and prevent SLA violations by determining if the migration of virtual machines or workloads to new physical machines within virtualized environments meets predefined utilization and response time thresholds, ensuring compliance with SLA parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If workload migration is performed in virtualized environment, then high availability and flexibility are improved, but SLA violation risk increases
Solution Approach 1:
The system performs preliminary evaluation of SLA compliance before executing workload migration. It calculates capacity factors, service rates, and utilization thresholds in advance to predict whether the target infrastructure can meet SLA requirements, preventing SLA violations before they occur
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring workload performance metrics and comparing them against SLA thresholds. It uses this feedback to adjust migration decisions dynamically, ensuring SLA compliance while enabling workload mobility
2Measurement precision
If capacity estimation is performed through empirical trial and error method, then infrastructure capacity can be determined, but time consumption increases and capacity overestimation occurs
Solution Approach 1:
The system replaces empirical trial-and-error methods with analytical calculation models. It uses mathematical formulas to compute capacity factors, service rates, and utilization thresholds based on system parameters, providing accurate capacity estimation without time-consuming experiments
Solution Approach 2:
The system performs capacity estimation calculations in advance before migration decisions are made. By pre-calculating the required infrastructure capacity using analytical models, it eliminates the need for time-consuming trial-and-error testing while ensuring accurate capacity planning
3Productivity
If virtualization layer is introduced, then resource utilization efficiency is improved, but performance prediction difficulty increases
Solution Approach 1:
The system transforms complex virtualized environment performance prediction into manageable calculations by identifying and monitoring key parameters such as capacity factor, service rate, and utilization threshold. By focusing on these critical parameters, it simplifies performance prediction while maintaining accuracy in virtualized environments
Data Source
AI summary
This technique determines the possible Service Level Agreement (SLA) violation during migrating a workload from a physical environment to a virtualized environment and also migrating a virtual machine (VM) from one physical machine to another within a virtualized environment. This technique uses capacity factor, i.e. the ratio of host physical machine (host PM) capacity and target physical machine (target PM) capacity, to determine the service rate change in the target PM compared to host PM and eventually calculates the VM utilization and response time in the target PM. It then checks if the VM utilization and response time in the target PM lies within the SLA limit. It further checks if the migration in the target virtualized PM is violating a predefined target PM utilization threshold or not and finally causes the migration in the target physical machine if all the SLA parameters are satisfied.